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Argonne National Laboratory’s Accelerator Science Division is seeking a Postdoctoral Appointee to contribute to the development of a Sub- THz Collinear Structural Wakefield Accelerator
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), and cell free methods. Key Responsibilities: Development and optimization of vector constructs and expression condition characterization of protein yields and quality, and large-scale protein production
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A postdoc position is immediately available at the Advanced Photon Source of Argonne National Laboratory. The postdoctoral appointee will develop ultrafast microscale photonics and MEMS
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focuses on developing a cutting-edge hybrid quantum computing platform that integrates entangled superconducting qubits with single electron-on-neon (eNe) qubits. Key Responsibilities: Design and fabricate
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We are seeking a highly motivated postdoctoral researcher to join the Center for Nanoscale Materials (CNM) at Argonne National Laboratory. The successful candidate will contribute to the development
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High-Energy Physics (HEP). We seek highly qualified candidates with interest and experience in ML algorithms including unsupervised techniques, time-series modeling, and clustering algorithms
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Knowledge in modeling and algorithms for large-scale ordinary differential equations (ODEs) and differential-algebraic equations (DAEs) Proficiency in a scientific programming language (e.g., C, C++, Fortran
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The Energy Systems and Infrastructure Assessment (ESIA) division at Argonne provides the rationale for decision makers to improve energy efficiency. ESIA develops and uses analytic tools to help
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an exciting approach to agentic, fully autonomous thin film development using a combination of automated electroplating, in-operando measurements, and AI driven algorithms. He or she will work with a team of
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electron beams, advanced beam-manipulation for precise electron-beam shaping, and ML for accelerator science. Responsibilities Develop and deploy ML algorithms for autonomous operations and optimization